A coordinate-transformed Arnoldi algorithm for generating guaranteed stable reduced-order models of RLC circuits

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A coordinate-transformed Arnoldi algorithm for generating guaranteed stable reduced-order models of RLC circuits

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International Conference on Computer Aided Design archive
Proceedings of the 1996 IEEE/ACM international conference on Computer-aided design table of contents

San Jose, California, United States

Pages: 288 - 294

Year of Publication: 1997

ISBN:0-8186-7597-7

Authors

L. Miguel Silveira	IST/INESC, Cadence European Labs, Av. Alves Redol, 9, 1000 Lisboa, Portugal
Mattan Kamon	Research Laboratory of Electronics, Dept. of Electrical Eng. and Comp. Science, Massachusetts Institute of Technology, Cambridge, MA
Ibrahim Elfadel	Research Laboratory of Electronics, Dept. of Electrical Eng. and Comp. Science, Massachusetts Institute of Technology, Cambridge, MA and Department of VLSI CAD and Verification, IBM T. J. Watson Research Center, Yorktown, NY.
Jacob White	Research Laboratory of Electronics, Dept. of Electrical Eng. and Comp. Science, Massachusetts Institute of Technology, Cambridge, MA

Sponsors

IEEE-CS : Computer Society
IEEE-CAS : Circuits & Systems
SIGDA: ACM Special Interest Group on Design Automation

Publisher

IEEE Computer Society Washington, DC, USA

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Downloads (6 Weeks): 3, Downloads (12 Months): 14, Citation Count: 40

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ABSTRACT

Since the first papers on asymptotic waveform evaluation (AWE), Pade-based reduced order models have become standard for improving coupled circuit-interconnect simulation efficiency. Such models can be accurately computed using bi-orthogonalization algorithms like Pade via Lanczos (PVL), but the resulting Pade approximates can still be unstable even when generated from stable RLC circuits. For certain classes of RC circuits it has been shown that congruence transforms, like the Arnoldi algorithm, can generate guaranteed stable and passive reduced-order models. In this paper we present a computationally efficient model-order reduction technique, the coordinate-transformed Arnoldi algorithm, and show that this method generates arbitrarily accurate and guaranteed stable reduced-order models for RLC circuits. Examples are presented which demonstrates the enhanced stability and efficiency of the new method.

REFERENCES

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